Stochastic discrete epidemic modeling of COVID-19 transmission in the Province of Shaanxi incorporating public health intervention and case importation

Sanyi Tang; Biao Tang; Nicola Luigi Bragazzi; Fan Xia; Tangjuan Li; Sha He; Pengyu Ren; Xia Wang; Zhihang Peng; Yanni Xiao; Jianhong Wu

Since the Spring Festival holiday most people have been at home, when do they return back to work/study is a challenging problem. Consequently, we investigate the effect of population movement on infections, especially on the possibility of inducing the second outbreak. To this end, we initially estimate the unknown parameters by least square methods, listed in Table 1 , by fitting the discrete stochastic model to the traced data between January 10 th to February 7 th (purple curve with dots), and by using the mean parameter values of 1000 times of least square estimations (listed in Table 1 ) we get 500 stochastic trajectories of model (1), as shown in Figure 8 (A-C). To investigate the effect of resumption of work on the epidemic, especially on possible second outbreak, by which we may suggest the public health sectors when workers can return back to Shaanxi, we predicate the disease infection by using the data on imported cases and moving from other cities to Shaanxi province (shown in Figure 2 ). Suppose population to start to return back to Shannxi province from February 24 th to March 9 th , 2020, we can see from Figure 9 the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.